measurementInvarianceTable: Measurement invariance table.
In psytabs: Produce well-formatted tables for psychological research
Description
Usage
Arguments
Details
Value
Examples
Description
Produces a table summarizing the results of a measurement invariance analysis as conducted by the respective function of the lavaan and semTools package.
Usage
1
measurementInvarianceTable(measurement.invariance)
Arguments
measurement.invariance
Results returned by the measurementInvariance function of the lavaan or semTools package.
Details
Please note that if the scaled chi-squared statistic is used a special chi-squared difference test is calculated, because the difference between two scaled chi-square statistics does not follow the chi-squared distribution. See also http://www.statmodel.com/chidiff.shtml.
Value
A measurement invariance table.
Examples
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library(semTools)
#Example taken from the semTools package
HW.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
mi.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, group="school")
tab.1 <- measurementInvarianceTable(mi.result)
tab.1
mi.strict.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, strict=TRUE, group="school")
tab.2 <- measurementInvarianceTable(mi.strict.result)
tab.2
mi.robust.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, estimator="MLM", group="school")
tab.3 <- measurementInvarianceTable(mi.robust.result)
tab.3
mi.robstrict.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, estimator="MLM", strict=TRUE, group="school")
tab.4 <- measurementInvarianceTable(mi.robstrict.result)
tab.4
#saveTable(tab.2, "measurementInvarianceTable.rtf")
Example output
Loading required package: lavaan
This is lavaan 0.5-23.1097
lavaan is BETA software! Please report any bugs.
###############################################################################
This is semTools 0.4-14
All users of R (or SEM) are invited to submit functions or ideas for functions.
###############################################################################
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.means
Chi Square Difference Test
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 8.192 6 0.2244
fit.intercepts 60 7508.6 7686.6 164.10 40.059 6 4.435e-07 ***
fit.means 63 7543.1 7710.0 204.61 40.502 3 8.338e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi rmsea cfi.delta rmsea.delta
fit.configural 0.923 0.097 NA NA
fit.loadings 0.921 0.093 0.002 0.004
fit.intercepts 0.882 0.107 0.038 0.015
fit.means 0.840 0.122 0.042 0.015
chi2 df Dchi2 Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 115.9 48 NA NA NA 0.923 NA 0.097 NA 7706.8 NA
Metric 124.0 54 8.2 6 0.224 0.921 0.002 0.093 0.004 7680.8 26.1
Scalar 164.1 60 40.1 6 0.000 0.882 0.038 0.107 -0.015 7686.6 -5.8
Mean 204.6 63 40.5 3 0.000 0.840 0.042 0.122 -0.015 7710.0 -23.4
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.residuals
Model 5 : fit.means
Chi Square Difference Test
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 8.192 6 0.22436
fit.intercepts 60 7508.6 7686.6 164.10 40.059 6 4.435e-07 ***
fit.residuals 69 7508.1 7652.6 181.51 17.409 9 0.04269 *
fit.means 72 7541.9 7675.3 221.34 39.824 3 1.161e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi rmsea cfi.delta rmsea.delta
fit.configural 0.923 0.097 NA NA
fit.loadings 0.921 0.093 0.002 0.004
fit.intercepts 0.882 0.107 0.038 0.015
fit.residuals 0.873 0.104 0.009 0.003
fit.means 0.831 0.117 0.042 0.013
chi2 df Dchi2 Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 115.9 48 NA NA NA 0.923 NA 0.097 NA 7706.8 NA
Metric 124.0 54 8.2 6 0.224 0.921 0.002 0.093 0.004 7680.8 26.1
Scalar 164.1 60 40.1 6 0.000 0.882 0.038 0.107 -0.015 7686.6 -5.8
Residual 181.5 69 17.4 9 0.043 0.873 0.009 0.104 0.003 7652.6 34.0
Mean 221.3 72 39.8 3 0.000 0.831 0.042 0.117 -0.013 7675.3 -22.7
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.means
Scaled Chi Square Difference Test (method = "satorra.bentler.2001")
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 7.136 6 0.3085
fit.intercepts 60 7508.6 7686.6 164.10 54.934 6 4.78e-10 ***
fit.means 63 7543.1 7710.0 204.61 89.525 3 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi.scaled rmsea.scaled cfi.scaled.delta rmsea.scaled.delta
fit.configural 0.914 0.094 NA NA
fit.loadings 0.913 0.089 0.001 0.005
fit.intercepts 0.863 0.106 0.050 0.017
fit.means 0.806 0.123 0.057 0.017
chi2S df Dchi2S Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 111.7 48 NA NA NA 0.914 NA 0.094 NA 7706.8 NA
Metric 118.2 54 7.1 6 0.308 0.913 0.001 0.089 0.005 7680.8 26.1
Scalar 161.3 60 54.9 6 0.000 0.863 0.050 0.106 -0.017 7686.6 -5.8
Mean 206.6 63 89.5 3 0.000 0.806 0.057 0.123 -0.017 7710.0 -23.4
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.residuals
Model 5 : fit.means
Scaled Chi Square Difference Test (method = "satorra.bentler.2001")
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 7.136 6 0.30846
fit.intercepts 60 7508.6 7686.6 164.10 54.934 6 4.78e-10 ***
fit.residuals 69 7508.1 7652.6 181.51 16.451 9 0.05804 .
fit.means 72 7541.9 7675.3 221.34 90.961 3 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi.scaled rmsea.scaled cfi.scaled.delta rmsea.scaled.delta
fit.configural 0.914 0.094 NA NA
fit.loadings 0.913 0.089 0.001 0.005
fit.intercepts 0.863 0.106 0.050 0.017
fit.residuals 0.853 0.102 0.010 0.004
fit.means 0.797 0.118 0.056 0.015
chi2S df Dchi2S Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 111.7 48 NA NA NA 0.914 NA 0.094 NA 7706.8 NA
Metric 118.2 54 7.1 6 0.308 0.913 0.001 0.089 0.005 7680.8 26.1
Scalar 161.3 60 54.9 6 0.000 0.863 0.050 0.106 -0.017 7686.6 -5.8
Residual 177.5 69 16.5 9 0.058 0.853 0.010 0.102 0.004 7652.6 34.0
Mean 221.7 72 91.0 3 0.000 0.797 0.056 0.118 -0.015 7675.3 -22.7
psytabs documentation built on May 2, 2019, 5:27 p.m.
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Description Usage Arguments Details Value Examples
Description
Produces a table summarizing the results of a measurement invariance analysis as conducted by the respective function of the lavaan and semTools package.
Usage
1 | measurementInvarianceTable(measurement.invariance)
|
Arguments
measurement.invariance |
Results returned by the measurementInvariance function of the lavaan or semTools package. |
Details
Please note that if the scaled chi-squared statistic is used a special chi-squared difference test is calculated, because the difference between two scaled chi-square statistics does not follow the chi-squared distribution. See also http://www.statmodel.com/chidiff.shtml.
Value
A measurement invariance table.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | library(semTools)
#Example taken from the semTools package
HW.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
mi.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, group="school")
tab.1 <- measurementInvarianceTable(mi.result)
tab.1
mi.strict.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, strict=TRUE, group="school")
tab.2 <- measurementInvarianceTable(mi.strict.result)
tab.2
mi.robust.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, estimator="MLM", group="school")
tab.3 <- measurementInvarianceTable(mi.robust.result)
tab.3
mi.robstrict.result <- measurementInvariance(HW.model, data=HolzingerSwineford1939, estimator="MLM", strict=TRUE, group="school")
tab.4 <- measurementInvarianceTable(mi.robstrict.result)
tab.4
#saveTable(tab.2, "measurementInvarianceTable.rtf")
|
Example output
Loading required package: lavaan
This is lavaan 0.5-23.1097
lavaan is BETA software! Please report any bugs.
###############################################################################
This is semTools 0.4-14
All users of R (or SEM) are invited to submit functions or ideas for functions.
###############################################################################
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.means
Chi Square Difference Test
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 8.192 6 0.2244
fit.intercepts 60 7508.6 7686.6 164.10 40.059 6 4.435e-07 ***
fit.means 63 7543.1 7710.0 204.61 40.502 3 8.338e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi rmsea cfi.delta rmsea.delta
fit.configural 0.923 0.097 NA NA
fit.loadings 0.921 0.093 0.002 0.004
fit.intercepts 0.882 0.107 0.038 0.015
fit.means 0.840 0.122 0.042 0.015
chi2 df Dchi2 Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 115.9 48 NA NA NA 0.923 NA 0.097 NA 7706.8 NA
Metric 124.0 54 8.2 6 0.224 0.921 0.002 0.093 0.004 7680.8 26.1
Scalar 164.1 60 40.1 6 0.000 0.882 0.038 0.107 -0.015 7686.6 -5.8
Mean 204.6 63 40.5 3 0.000 0.840 0.042 0.122 -0.015 7710.0 -23.4
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.residuals
Model 5 : fit.means
Chi Square Difference Test
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 8.192 6 0.22436
fit.intercepts 60 7508.6 7686.6 164.10 40.059 6 4.435e-07 ***
fit.residuals 69 7508.1 7652.6 181.51 17.409 9 0.04269 *
fit.means 72 7541.9 7675.3 221.34 39.824 3 1.161e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi rmsea cfi.delta rmsea.delta
fit.configural 0.923 0.097 NA NA
fit.loadings 0.921 0.093 0.002 0.004
fit.intercepts 0.882 0.107 0.038 0.015
fit.residuals 0.873 0.104 0.009 0.003
fit.means 0.831 0.117 0.042 0.013
chi2 df Dchi2 Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 115.9 48 NA NA NA 0.923 NA 0.097 NA 7706.8 NA
Metric 124.0 54 8.2 6 0.224 0.921 0.002 0.093 0.004 7680.8 26.1
Scalar 164.1 60 40.1 6 0.000 0.882 0.038 0.107 -0.015 7686.6 -5.8
Residual 181.5 69 17.4 9 0.043 0.873 0.009 0.104 0.003 7652.6 34.0
Mean 221.3 72 39.8 3 0.000 0.831 0.042 0.117 -0.013 7675.3 -22.7
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.means
Scaled Chi Square Difference Test (method = "satorra.bentler.2001")
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 7.136 6 0.3085
fit.intercepts 60 7508.6 7686.6 164.10 54.934 6 4.78e-10 ***
fit.means 63 7543.1 7710.0 204.61 89.525 3 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi.scaled rmsea.scaled cfi.scaled.delta rmsea.scaled.delta
fit.configural 0.914 0.094 NA NA
fit.loadings 0.913 0.089 0.001 0.005
fit.intercepts 0.863 0.106 0.050 0.017
fit.means 0.806 0.123 0.057 0.017
chi2S df Dchi2S Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 111.7 48 NA NA NA 0.914 NA 0.094 NA 7706.8 NA
Metric 118.2 54 7.1 6 0.308 0.913 0.001 0.089 0.005 7680.8 26.1
Scalar 161.3 60 54.9 6 0.000 0.863 0.050 0.106 -0.017 7686.6 -5.8
Mean 206.6 63 89.5 3 0.000 0.806 0.057 0.123 -0.017 7710.0 -23.4
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.residuals
Model 5 : fit.means
Scaled Chi Square Difference Test (method = "satorra.bentler.2001")
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 48 7484.4 7706.8 115.85
fit.loadings 54 7480.6 7680.8 124.04 7.136 6 0.30846
fit.intercepts 60 7508.6 7686.6 164.10 54.934 6 4.78e-10 ***
fit.residuals 69 7508.1 7652.6 181.51 16.451 9 0.05804 .
fit.means 72 7541.9 7675.3 221.34 90.961 3 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Fit measures:
cfi.scaled rmsea.scaled cfi.scaled.delta rmsea.scaled.delta
fit.configural 0.914 0.094 NA NA
fit.loadings 0.913 0.089 0.001 0.005
fit.intercepts 0.863 0.106 0.050 0.017
fit.residuals 0.853 0.102 0.010 0.004
fit.means 0.797 0.118 0.056 0.015
chi2S df Dchi2S Ddf Dpval cfi Dcfi rmsea Drmsea bic Dbic
Configural 111.7 48 NA NA NA 0.914 NA 0.094 NA 7706.8 NA
Metric 118.2 54 7.1 6 0.308 0.913 0.001 0.089 0.005 7680.8 26.1
Scalar 161.3 60 54.9 6 0.000 0.863 0.050 0.106 -0.017 7686.6 -5.8
Residual 177.5 69 16.5 9 0.058 0.853 0.010 0.102 0.004 7652.6 34.0
Mean 221.7 72 91.0 3 0.000 0.797 0.056 0.118 -0.015 7675.3 -22.7
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